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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Decarbonizing agriculture through the conversion of animal manure to dietary protein and ammonia fertilizer

The decarbonization of agriculture faces many challenges and has received a level of attention insufficient to abate the worst effects of climate change and ensure a sustainable bioeconomy. Agricultural emissions are caused both by fossil-intensive fertilizer use and land-use change, which in turn are driven in part by increasing demand for dietary protein. To address this challenge, we present a synergistic system in which organic waste-derived biogas (a mixture of methane and carbon dioxide) is converted to dietary protein and ammonia fertilizer. This system produces low-carbon fertilizer inputs alongside high-quality protein, addressing the primary drivers of agricultural emissions. If the proposed system were implemented across the United States utilizing readily available organic waste from municipal wastewater, landfills, animal manure, and commercial operations, we estimate 30% of dietary protein intake and 127% of ammonia usage could be displaced while reducing land use, water consumption, and greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Opportunities and challenges for flow-through hydrothermal pretreatment in advanced biorefineries

Hydrothermal pretreatment (HTP) using only water offers great potential to reduce the overall cost of the bioconversion process. However, traditional HTP performed in a batch has limitations in removing lignin and often needs to be performed under severe conditions to achieve reasonable pretreatment effects. Additionally, lignin left in the pretreated residue at these conditions is also highly condensed, thus possessing an even more adverse impact on the hydrolysis process, which requires high enzyme loadings. To address these technical challenges, HTP performed in a flow-through configuration was developed to simultaneously achieve near-complete hemicellulose recovery, high lignin removal and high sugar release. Despite facing challenges such as potentially large water usage, flow-through HTP still represents one of the most cost-effective and eco-friendly pretreatment methods. This review mainly covers the latest cutting-edge innovations of flow-through HTP along with structural and compositional changes of cellulose, hemicellulose, and lignin before and after pretreatment.

09 BIOMASS FUELS↗
DOE OSTI2026

Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance

Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET derived 3D segmented volumes as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the “dark complex,” modulate metabolic flux at a conserved regulatory node of the Calvin–Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4.

Johnson, Connah G.↗
DOE OSTI2020

Regional difference and related cooling electricity savings of air pollutant affected natural ventilation in commercial buildings across the US

Maintaining indoor air pollutants under acceptable levels is significant to protect occupants from exposure to excessive air pollutants in natural ventilation. In this paper, using the representative air pollutant concentration data, we present the natural ventilation usability with associated cooling energy saving potentials in different location settings (urban and city center, suburban and rural) of the US under the influence of local weather conditions and major outdoor air pollutants, i.e. PM2.5, PM10 and ozone. It is found that the impacts of air pollutants on natural ventilation are usually higher in urban/suburban areas than rural areas (up to 25% difference) with the PM2.5 being the most significant outdoor air pollutant affecting natural ventilation usage. Furthermore, ozone could become increasingly influential on natural ventilation as moving from urban to suburban/rural areas. As to the cooling energy saving considering the impacts of outdoor air pollutants, natural ventilation is estimated to save approximately 10%–40% cooling energy (800–2600 kWh per small commercial building) annually in different location settings of investigated areas across the US. The following economic analysis demonstrates that these electricity savings lead to approximately 80–540 dollars annual savings of building operation cost per building. If the time of use rate is adopted, these cost savings could further increase by approximately 20% (Los Angeles) to more than 50% (Albuquerque) depending on different rate structures, which further demonstrates the potential of adopting natural ventilation as a sustainability measurement with benefits for building owners without compromising occupants health.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Modelling urban-scale occupant behaviour, mobility, and energy in buildings: A survey

The proliferation of urban sensing, IoT, and big data in cities provides unprecedented opportunities for a deeper understanding of occupant behaviour and energy usage patterns at the urban scale. This enables data-driven building and energy models to capture the urban dynamics, specifically the intrinsic occupant and energy use behavioural profiles that are not usually considered in traditional models. Although there are related reviews, none have investigated urban data for use in modelling occupant behaviour and energy use at multiple scales, from buildings to neighbourhood to city. This survey paper aims to fill this gap by providing a critical summary and analysis of the works reported in the literature. We present the different sources of occupant-centric urban data that are useful for data-driven modelling and categorise the range of applications and recent data-driven modelling techniques for urban behaviour and energy modelling, along with the traditional stochastic and simulation-based approaches. Finally, we present a set of recommendations for future directions in data-driven modelling of occupant behaviour and energy in buildings at the urban scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Dynamic metrics of natural ventilation cooling effectiveness for interactive modeling

The evaluation of natural ventilation potential for cooling indoor spaces during the early design phases is of great interest to researchers and practitioners. Among various definitions and usages for natural ventilation potential (NVP) in early design evaluation, this paper reviews and identifies the key performance indicators, and proposes two new dynamic metrics—natural ventilation cooling effectiveness (NVCE) and climate potential utilization ratio (CPUR). The metrics are dynamically responsive to various design options, in both steady and transient states, allowing consideration of thermal mass. Assisting in design development processes, the metrics quantify how well indoor spaces make use of natural ventilation’s cooling capacity. Case studies are presented to demonstrate how NVCE and CPUR enable designers to evaluate the predicted performance and how to apply the information to improve building design. Finally, the results of the design iterations showed that the relationship among various design parameters should be dynamically understood in order to evaluate the performance of natural ventilation, confirming that “the more the airflow, the greater the potential,” and “the heavier the thermal mass, the greater the energy saving” were not always true.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

SynopFrame: Multiscale time-dependent visual abstraction framework for analyzing DNA nanotechnology simulations

We present an open-source framework, SynopFrame, that allows DNA nanotechnology (DNA-nano) experts to analyze and understand molecular dynamics simulation trajectories of their designs. We use a multiscale multi-dimensional abstraction space, connect the representations to a projected conformational space plot of the structure’s temporal sequence, and thus enable experts to analyze the dynamics of their structural designs and, specifically, failure cases of the assembly. In addition, our time-dependent abstraction representation allows the biologists, for the first time in a smooth and structurally clear way, to identify and observe temporal transitions of a DNA-nano design from one configuration to another, and to highlight important periods of the simulation for further analysis. We realize SynopFrame as a dashboard of the different synchronized 3D spatial and 2D schematic visual representations, with a color overlay to show essential properties such as the status of hydrogen bonds. The linking of the spatial, schematic, and abstract views ensures that users can effectively analyze the high-frequency motion. We also categorize the status of the hydrogen bonds into a new format to allow us to color-encode it and overlay it on the representations. To demonstrate the utility of SynopFrame, we describe example usage scenarios and report user feedback.

Abstraction space↗
DOE OSTI2016

TOUGH3: A new efficient version of the TOUGH suite of multiphase flow and transport simulators

The TOUGH suite of nonisothermal multiphase flow and transport simulators has been updated by various developers over many years to address a vast range of challenging subsurface problems. The increasing complexity of the simulated processes as well as the growing size of model domains that need to be handled call for an improvement in the simulator's computational robustness and efficiency. Moreover, modifications have been frequently introduced independently, resulting in multiple versions of TOUGH that (1) led to inconsistencies in feature implementation and usage, (2) made code maintenance and development inefficient, and (3) caused confusion to users and developers. TOUGH3—a new base version of TOUGH—addresses these issues. It consolidates both the serial (TOUGH2 V2.1) and parallel (TOUGH2-MP V2.0) implementations, enabling simulations to be performed on desktop computers and supercomputers using a single code. New PETSc parallel linear solvers are added to the existing serial solvers of TOUGH2 and the Aztec solver used in TOUGH2-MP. The PETSc solvers generally perform better than the Aztec solvers in parallel and the internal TOUGH3 linear solver in serial. TOUGH3 also incorporates many new features, addresses bugs, and improves the flexibility of data handling. So due to the improved capabilities and usability, TOUGH3 is more robust and efficient for solving tough and computationally demanding problems in diverse scientific and practical applications related to subsurface flow modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Advanced data science toolkit for non-data scientists – A user guide

Emerging modern data analytics attracts much attention in materials research and shows great potential for enabling data-driven design. Data populated from the high-throughput CALPHAD approach enables researchers to better understand underlying mechanisms and to facilitate novel hypotheses generation, but the increasing volume of data makes the analysis extremely challenging. Here in this paper, we introduce an easy-to-use, versatile, and open-source data analytics frontend, ASCENDS (Advanced data SCiENce toolkit for Non-Data Scientists), designed with the intent of accelerating data-driven materials research and development. The toolkit is also of value beyond materials science as it can analyze the correlation between input features and target values, train machine learning models, and make predictions from the trained surrogate models of any scientific dataset. Various algorithms implemented in ASCENDS allow users performing quantified correlation analyses and supervised machine learning to explore any datasets of interest without extensive computing and data science background. The detailed usage of ASCENDS is introduced with an example of experimental high-temperature alloy data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Operando carbon corrosion measurements in fuel cells using boron-doped carbon supports

Carbonaceous materials are the most common catalyst supports in proton exchange membrane fuel cell (PEMFCs), yet their corrosion is one of the limiting factors in achieving high durability. Herein, we doped carbon supports with boron (B) to increase the corrosion-resistance of the support. Two types of B-doped carbons were synthesized and studied as platinum support materials. Further, they varied in their morphologies, surface areas, and the types of boron species. The durability of Pt/B-doped carbon catalysts was investigated using the US-DOE catalysts’ supports accelerated stress test (AST) and a mass-spectrometer connected to the fuel cell effluent stream to quantify the mass of corroded carbon support in operando. The addition of boron to the carbon increased the stability of Pt catalysts in long-term usage of PEMFC. After 4000 AST cycles, more than 50% of initial current density was preserved for the boron-containing systems, while less than 30% of it remained with Vulcan carbon (Pt/V). Also, the Pt/B-doped carbon samples demonstrated better electrochemical active surface area (ECSA) stability when compared to Pt/V. Carbon loss measurements showed that B-doped carbons have higher resistance to electrochemical corrosion than unmodified carbon. Specifically, the substitutional boron-doped carbon demonstrated an extremely high stability and low corrosion rate.

25 ENERGY STORAGE↗
DOE OSTI2021

From inert gas to fertilizer, fuel and fine chemicals: N 2 reduction and fixation

The 100th anniversary of a leading nitrogen fixation technology developer like CASALE SA is a reason to reflect over the 20th century successful solution of the problem of world food supply, and to look out for solutions for sustainable developments with respect to ammonia production. Here, we review the role of nitrogen as essential chemical constituent in photosynthesis and biology, and component of ammonia as it is used as fertilizer for primary production by photosynthesis for farming and food supply and its future role as energy carrier. While novel synthesis methods and very advanced synchrotron based x-ray analytical techniques are being developed, we feel it is important to refer to the historical and economical context of nitrogen. The breaking of the N≡N triple bond remains a fundamental chemical and energetic problem in this context. We review the electrochemical ammonia synthesis as an energetically and environmentally benign method. Two relatively novel X-ray spectroscopy methods, which are relevant for the molecular understanding of the catalysts and biocatalysts, i.e. soft X-ray absorption spectroscopy and nuclear resonant vibration spectroscopy are presented. We illustrate the perceived reality in fertilizer usage on the field, and fertilizer production in the factory complex with photos and thus provide a contrast to the academic view of the molecular process of ammonia function and production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modelling a compressible packed bed flow-through washing and deacetylation reactor for corn stover pretreatment

The deacetylation process is a key step in the lignocellulosic biomass pretreatment process that currently is done in batch reactors. A flow-through diffuser type reactor is a promising approach to make the process more efficient and economically favorable. A washing step before deacetylation can further reduce chemical usage and increase the process efficiency. However, the highly compacted biomass particles can cause significant pressure-drop for fluid flow through the bed, which in the worst case can cause self-enhancing pressure-drop leading to reactor blocking. Detailed understanding of the fundamentals of flow through a compressible packed bed is necessary to scale up the washing and deacetylation process. This work closely examines the classical Kozeny Carman equation and proposes modifications to accurately predict the pressure-drop at different compaction states. Here, a compressible packed bed model is further developed based on the interaction between solid mechanics and fluid dynamics. Experimental measurements of water flow through a packed bed of corn stover show good agreement with the developed model. Corn stover washing process scale up simulations show that smaller reactor diameter, higher friction lining material, lower process throughput, and higher process temperature is favorable in stabilizing the bed from extensive compression when the bed height is fixed.

09 BIOMASS FUELS↗
DOE OSTI2021

Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity

SARS-CoV-2 can mutate and evade immunity, with consequences for efficacy of emerging vaccines and antibody therapeutics. Here, we demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is a highly variable region of S and provide epidemiological, clinical, and molecular characterization of a prevalent, sentinel RBM mutation, N439K. We demonstrate N439K S protein has enhanced binding affinity to the hACE2 receptor, and N439K viruses have similar in vitro replication fitness and cause infections with similar clinical outcomes as compared to wild type. We show the N439K mutation confers resistance against several neutralizing monoclonal antibodies, including one authorized for emergency use by the US Food and Drug Administration (FDA), and reduces the activity of some polyclonal sera from persons recovered from infection. Immune evasion mutations that maintain virulence and fitness such as N439K can emerge within SARS-CoV-2 S, highlighting the need for ongoing molecular surveillance to guide development and usage of vaccines and therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Dynamic genetic adaptation of Bacteroides thetaiotaomicron during murine gut colonization

To understand how a bacterium ultimately succeeds or fails in adapting to a new host, it is essential to assess the temporal dynamics of its fitness over the course of colonization. Here, we introduce a human-derived commensal organism, Bacteroides thetaiotaomicron (Bt), into the guts of germ-free mice to determine whether and how the genetic requirements for colonization shift over time. Combining a high-throughput functional genetics assay and transcriptomics, we find that gene usage changes drastically during the first days of colonization, shifting from high expression of amino acid biosynthesis genes to broad upregulation of diverse polysaccharide utilization loci. Within the first week, metabolism becomes centered around utilization of a predominant dietary oligosaccharide, and these changes are largely sustained through 6 weeks of colonization. Spontaneous mutations in wild-type Bt also evolve around this locus. These findings highlight the importance of considering temporal colonization dynamics in developing more effective micro biome-based therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Upcycling mixed cathode materials to high-energy-density LiFe 0.75 Mn 0.25 PO 4

To address the demand for next-generation cathode materials with high energy density, upcycling LiFePO 4 into LiFe 0.75 Mn 0.25 PO 4 has attracted considerable attention. Nevertheless, existing strategies have yet to achieve both morphology and full elemental recovery under mild ambient conditions. Here, we report an upcycling route that can address this issue by combining leaching and a high-temperature treatment process. The upcycled LiFe 0.75 Mn 0.25 PO 4 exhibits enlarged lattice spacing and a high discharge plateau, and it delivers an energy density of 563.7 Wh/kg, 40.3 Wh/kg higher than recycled LiFePO 4 , which indicates the high value of the proposed upcycling strategy. At 1 C, LiFe 0.75 Mn 0.25 PO 4 also exhibits excellent cycling stability of 91% over 700 cycles. Techno-economic analysis also indicates impressive economic and environmental benefits, including 10.4% less raw materials usage and 12.2% less energy consumption and wastewater generation. This work demonstrates a scalable and economic upcycling strategy and provides a promising pathway for sustainable battery upcycling compatible with industrial conditions.

LMFP↗
DOE OSTI2018

A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning

Many geological materials, such as shale, mudstone, carbonate rock, limestone and rock salt are multi-porosity porous media in which pores of different scales may co-exist in the host matrix. When fractures propagate in these multi-porosity materials, these pores may enlarge and coalesce and therefore change the magnitude and the principal directions of the effective permeability tensors. The pore-fluid inside the cracks and the pores of host matrix may interact and exchange fluid mass, but the difference in hydraulic properties of these pores often means that a single homogenized effective permeability tensor field is insufficient to characterize the evolving hydraulic properties of these materials at smaller time scale. Furthermore, the complexity of the hydro-mechanical coupling process and the induced mechanical and hydraulic anisotropy originated from the micro-fracture and plasticity at grain scale also makes it difficult to propose, implement and validate separated macroscopic constitutive laws for numerical simulations. Here this article presents a hybrid data-driven method designed to capture the multiscale hydro-mechanical coupling effect of porous media with pores of various different sizes. At each scale, data-driven models generated from supervised machine learning are hybridized with classical constitutive laws in a directed graph that represents the numerical models. By using sub-scale simulations to generate database to train material models, an offline homogenization procedure is used to replace the up-scaling procedure to generate cohesive laws for localized physical discontinuities at both grain and specimen scales. Through a proper homogenization procedure that preserves spatial length scales, the proposed method enables field-scale simulations to gather insights from meso-scale and grain-scale micro-structural attributes. This method is proven to be much more computationally efficient than the classical DEM–FEM or FEM2 approach while at the same time more robust and flexible than the classical surrogate modeling approach. Due to the usage of bridging-scale technique, the proposed model may provide multiple opportunities to incorporate different types of simulations and experimental data across different length scales for machine learning. Numerical issues will also be discussed.

42 ENGINEERING↗
DOE OSTI2024

Symbolic construction of the chemical Jacobian of quasi-steady state (QSS) chemistries for Exascale computing platforms

The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of chemical mechanisms for implementation in computational reacting flow solvers. However, for many applications, the resulting model still requires implicit methods for efficient time integration. Here, in this paper, we outline an approach to formulating the QSSA reduction that is coupled with a strategy to generate C++ source code to evaluate the net species production rates, and the chemical Jacobian. The code-generation component employs a symbolic approach enabling a simple and effective strategy to analytically compute the chemical Jacobian. For computational tractability, the symbolic approach needs to be paired with common subexpression elimination which can negatively affect memory usage. Several solutions are outlined and successfully tested on a 3D multipulse ignition problem, thus allowing portable application across chemical model sizes and GPU capabilities. The implementation of the proposed method is available at https://github.com/AMReX-Combustion/PelePhysics under an open-source license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗